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Analisis Pengaruh Faktor Sosial Ekonomi Terhadap Akses Sanitasi Layak di Indonesia Tahun 2021 Widyastuti, Dyah; Jamaluddin, Halim Nur; Arisanti, Rohimma; Kartiasih, Fitri
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1853

Abstract

Access to sanitation is a fundamental component of health. Poor sanitation can reduce human welfare and hinder a country's socio-economic development. Therefore, access to adequate and equitable sanitation for all is a target to be achieved by 2030. This study aims to analyze the influence of socioeconomic factors on access to proper sanitation in Indonesia in 2021. The method used includes descriptive analysis in the form of graphs and data center sizes as well as inferential analysis with multiple linear regression. The results showed that the level of completion of high school and owning a latrine significantly increased access to proper sanitation. Conversely, the share of food expenditure significantly reduces access to proper sanitation. The government must prioritize sustainable education by expanding scholarship programs and also boosting financial support for the construction of sanitation facilities. To raise public awareness, there has to be more socialization and teaching about the value of good sanitation.
Pemodelan Status Ketertinggalan Perekonomian Regional Menggunakan Geographically Weighted Logistic Regression (GWLR) Bani Syafii, Ghulam An-Nabalah; Hanifah, Ria Dini; Arisanti, Rohimma; Pusponegoro, Novi Hidayat
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2208

Abstract

The goal of economic development is to improve the well-being of the people. However, economic development, especially in developing countries, including Indonesia, has been hampered by interregional disparities. This inequality leads to a grouping of economically backward people. This research aims to find out the general picture and identify the presence of spatial aspects on the status of the regional economy backwardness and the factors that influence it from the production side. Because there are indications of dependency and spatial heterogeneity, the study uses the Geographically Weighted Logistic Regression (GWLR) model. The results show that the rise in capital and the decrease in labor will lower the tendency for one to be categorized as a backward region. Therefore, investment needs to be intensified in industries in Indonesia and it is necessary to improve the quality of technologically literate human resources to streamline the production process.
HIERARCHICAL BAYESIAN SMALL AREA ESTIMATION ON OVERDISPERSED DATA: WORKERS WITH DISABILITIES IN INDONESIA Muhammad, Danardana; Jamaluddin, Halim Nur; Octavia, Mira; Arisanti, Rohimma; Istiana, Nofita
Journal of Fundamental Mathematics and Applications (JFMA) Vol 8, No 2 (2025)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jfma.v0i0.28526

Abstract

Persons with disabilities encounterdifficulties in accessing essentialservices, including employment, healthcare, information, and political participation. In line with the target 8.5 of the SDGs, efforts have been made to promotefull, productive, and decent employment for all, including for persons with disabilities. However, the majority ofworkers with disabilities in Indonesia remain concentrated in the informal sector during the period of 2022–2023. Unfortunately, data on workers with disabilities is currently only available at the national level. This limitation arises because the sample size of workers with disabilities is insufficient to meet the minimum requirements for direct estimation at the provincial level. Therefore, a Small Area Estimation approach is necessary to assess the participationof persons with disabilities in the workforce at more granular level, such as provinces. In this study, auxiliary variables such as the sex ratio, the number of residents who are shackled, and the availability of computer skills infrastructure were incorporated to the Small Area Estimation (SAE) framework. The Hierarchical Bayesian Poisson-Gamma was employed to improve the precision of direct estimation. The research results show that the HB Poisson-gamma estimator has better precision compared to the direct estimator.